Kunio takezawa wrote:
> R-users
> E-mail: r-help@r-project.org
>
> I have a quenstion on "gam()" in "gam" package.
> The help of gam() says:
> 'gam' uses the _backfitting
> algorithm_ to combine different smoothing or fitting methods.
>
> On the other hand, lm.wfit(), which is a routine of gam.fit() contains:
>
> z <- .Fortran("dqrls", qr = x * wts, n = n, p = p, y = y *
> wts, ny = ny, tol = as.double(tol), coefficients = mat.or.vec(p,
> ny), residuals = y, effects = mat.or.vec(n, ny), rank = integer(1),
> pivot = 1:p, qraux = double(p), work = double(2 * p),
> PACKAGE = "base")
> It may indicate that QR decomposition is used to derive an additive model
> instead of backfitting.
> I am wondering if my guess is correct, or this "the _backfitting
> algorithm"
> has another meaning.
>
Please don't ask the same question multiple times!
And no, backfitting and QR are unrelated concepts. You need to read up
on the theory, there are two fundamental books: Hastie & Tibshirani (gam
package) and Simon Wood (mgcv package). Both are a bit much to ask to
have summarized in email.
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